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https://doi.org/10.5713/ab.24.0658    [Accepted] Published online March 31, 2025.
Evaluating effect of different dominance genotype encodings on genome-wide association studies and genomic selection
Xiangyu Dai1  , Jiakun Qiao1  , Zhiwei Long1  , Zhaoxuan Che1  , Fangjun Xu1  , Na Miao1  , Mengjin Zhu1,2,* 
1Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
2The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, China
Correspondence:  Mengjin Zhu, Tel: +86-27-87281306, Fax: +86-27-87280408, Email: zhumengjin@mail.hzau.edu.cn
Received: 20 September 2024   • Revised: 5 December 2024   • Accepted: 17 March 2025
Abstract
Objective
The quantification of dominance effects varies across different models, and the appropriate coding in genetic analyses remains debated. This study investigated several proposed dominance encoding methods, evaluating their performance in genetic analyses.
Methods
Three datasets, each representing the breeds Duroc, Landrace, and Yorkshire, were used in this study. We assessed heritability, genetic effects, and prediction accuracy in genomic selection (GS), as well as significant loci and statistical power in genome-wide association studies (GWAS).
Results
In GS, correlations among additive effects and among total genetic effects across models were high (0.9-1) under different dominance encodings for most traits, while only the (0, 1, 0) and (0, 2p, 4p-2) encodings maintained high correlations for all traits. The average prediction accuracy of the additive-dominance model with the (0, 1, 0) encoding increased by 2.79% and 1.69%, respectively, compared to the (0, 1, 1) and (0, 2p, 4p-2) encodings for all traits. In GWAS, the (0, 1, 0) encoding had higher statistical power compared to the (0, 1, 1) and (0, 2p, 4p-2) encodings, especially for rare variants. Additionally, different dominance encodings identified independent and distinct significant loci.
Conclusion
The (0, 1, 0) encoding method generally outperforms the others in genetic analyses, while alternative encodings provide complementary insights into dominance effects. These findings provide valuable guidance for selecting dominance encodings in genetic analyses.
Keywords: Dominance; Genome-wide Association Study; Genomic Selection; Genomic Prediction
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